In recent years, a technique called big data analysis is being put to practical use, which produces new value by analyzing an enormous amount of data relating to the social infrastructure such as social networking services, finance, medical care and traffic.
In big data analysis, amounts of input data collected from the social infrastructure and output data which are analysis results is extremely large, and continues to increase over time. A storage system plays an important role in an enterprise IT system as a platform for securely storing and managing such an enormous amount of big data.
For example, an enterprise providing cloud service constructs a storage system with resources which are required at the moment upon initial operation of service to reduce introduction cost. As the storage system, for example, a scale-out type storage system is employed. That is, when the service operates and an amount of utilization of resources increases, overall processing performance of the system is improved by increasing the number of storage apparatuses (nodes).
As one means for improving processing performance of the storage system, there can be cache control of the storage system. Concerning cache control, for example, a technique of PTL 1 is known. PTL 1 discloses controlling a cache size to be allocated as cache control.